Abstract
In a crowded city, directions and speed of vehicles are usually changed arbitrarily. Analyzing travel preferences of vehicle has become a focus of research as it helps to classify region of interest in city and can be used in personalized recommendation and many other areas of application. In this paper, a travel identification method based on vehicle speed and Accessory (ACC) State is proposed. Continuously classifying and merging the trajectory points in GPS data stream, the travel activities of vehicle is extracted. It can provide a basis of data for the research on hot spots and support the research and application of vehicle trajectory data mining in areas of intelligent transportation and logistics.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Deng, Z., Ji, M., Chen, W.: Coupling passive GPS tracking and web-based travel surveys. J. Transp. Syst. Eng. Inf. Technol. 10(2), 178–183 (2009)
Stopher, P., FitzGerald, C., Zhang, J.: Search for a global positioning system device to measure personal travel. Transp. Res. Part C 16, 350–369 (2008)
Zhang, B.: Research on the Simplification and Semantic Enhancement of GPS Temporal and Spatial Trajectory Data for Traffic Travel Survey. East China Normal University, Shanghai (2011)
Zhou, C., Frankowski, D., Ludford, P., et al.: Discovering personal gazetteers: an interactive clustering approach, pp. 266–273. ACM (2004)
Tietbohl, A., Bogorny, V., Kuijpers, B., et al.: A clustering-based approach for discovering interesting places in trajectories. In: SAC, pp. 863–868 (2008)
Zhang, J., Qiu, P., Xu, Z.: A method to identify trip based on the mobile phone positioning. J. Wuhan Univ. Technol. (Transp. Sci. Eng.) 37(5), 934–938 (2013)
Zou, Y., Wan, J., Xia, Y.: LBSN user movement trajectory clustering mining method based on road network. Appl. Res. Comput. 08(8), 102–110 (2013)
Xiao, Y., Zhang, Z., Yang, W.: Users’ mobility behaviours mining algorithm based on GPS trajectory. Comput. Appl. Softw. 32(11), 83–87 (2015)
Yuan, J., Zheng, Y., Xie, X.: Discovering regions of different functions in a city using human mobility and POIs. In: ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pp. 186–194 (2012)
Xue, A., Zhang, R., Zheng, Y., et al.: Destination prediction by sub-trajectory synthesis and privacy protection against such prediction. In: IEEE International Conference on Data Engineering, pp. 254–265 (2013)
Yuan, J., Zheng, Y., Xie, X., et al.: T-Drive: enhancing driving directions with taxi drivers’ intelligence. IEEE Trans. Knowl. Data Eng. 25(1), 220–232 (2013)
Zheng, Y., Xie, X.: Learning travel recommendations from user-generated GPS traces. ACM Trans. Intell. Syst. Technol. 2(1), 389–396 (2011)
Zheng, V., Zheng, Y., Xie, X., et al.: Collaborative location and activity recommendations with GPS history data. In: Proceeding of the 19th International Conference on World Wide Web (2010)
Ma, S., Zheng, Y., Wolfson, O.: T-share: a large-scale dynamic taxi ridesharing service. In: IEEE International Conference on Data Engineering, pp. 410–421 (2013)
Liu, Y., Kang, C., Gao, S., et al.: Understanding intra-urban trip patterns from taxi trajectory data. J. Geogr. Syst. 14(4), 463–483 (2012)
Yuan, N., Zheng, Y., Zhang, L., et al.: T-Finder: a recommender system for finding passengers and vacant taxis. IEEE Trans. Knowl. Data Eng. 25(10), 2390–2403 (2013)
Acknowledgments
This work was supported in part by the National High-tech R&D Program of China (863 Program) under Grant No. 2015AA015403, Science & Technology Pillar Program of Hubei Province under Grant No. 2014BAA146, Nature Science Foundation of Hubei Province under Grant No. 2015CFA059, Hubei Key Laboratory of Transportation Internet of Things under Grant No. 2015III015-B03 and CERNET Innovation Project under Grant No. NGII20151006.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Xiong, S., Kuang, L., Duan, P., Shi, W. (2016). Logistics Vehicle Travel Preference of Interest Points Based on Speed and Accessory State. In: Li, W., et al. Internet and Distributed Computing Systems. IDCS 2016. Lecture Notes in Computer Science(), vol 9864. Springer, Cham. https://doi.org/10.1007/978-3-319-45940-0_26
Download citation
DOI: https://doi.org/10.1007/978-3-319-45940-0_26
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-45939-4
Online ISBN: 978-3-319-45940-0
eBook Packages: Computer ScienceComputer Science (R0)